Exploring the Impact of AI on Candidate Selection: A Two-Phase Methodological Approach with CRITIC-WASPAS

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Data de publicação
2024
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Procedia Computer Science
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0
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Contreras Pinochet L.H.
Lopes N.S.
Onusic L.M.
dos Santos M.
Pardim V.I.
Neto Francischini A.S.
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© 2024 The Authors.This study investigates how AI technologies can improve the candidate selection process. It will also use the WASPAS method to analyze the criteria used during the selection stages, aiming to optimize the effectiveness of the process. The article employed a two-phase methodological approach to enhance candidate selection analysis. The CRITIC Method assigned weights to criteria, while the WASPAS Method ranked alternatives based on these weights. A sensitivity analysis, specifically for the WASPAS method, further assessed its robustness and consistency, providing a comprehensive view of the decision-making process. Twelve experienced professionals from various sectors, all decision-makers, participated in the research. As a result of the CRITIC method C5 (31.45%) ‘Data Confidentiality' is the most important criteria, followed by C1 (25.92%) ‘Justice'. Furthermore, in the selection process using AI with the WASPAS method, statements A14 and A15 stand out in the final stage, automating the identification of the most suitable candidates for the position and carefully evaluating them. Meanwhile, A9, in the cognitive and behavioral testing stage, is crucial for identifying promising candidates based on objective results, ensuring an accurate fit between candidate and position and increasing the efficiency of the selection process.
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AI Technologies , Candidate selection , CRITIC method , Decision-making process , Methodological approach , Optimisations , Selection stages , Sensitivity analyzes , Two phase , WASPAS method
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